The plant ‘Heat Rate’ (HR) is a measure of overall efficiency of a thermal power generating system. It depends on a large number of factors, some of which are non-measurable, while data relating to others are seldom available and recorded. However, coal quality (expressed in terms of ‘effective heat value’ (EHV) as kcal/kg) transpires to be one of the important factors that influences HR values and data on EHV are available in any thermal power generating system. In the present work, we propose a prediction interval of the HR values on the basis of only EHV, keeping in mind that coal quality is one of the important (but not the only) factors that have a pronounced effect on the combustion process and hence on HR. The underlying theory borrows the idea of providing simultaneous confidence interval (SCI) to the coefficients of a p-th p(≥1) order autoregressive model (AR(p)). The theory has been substantiated with the help of real life data from a power utility (after suitable base and scale transfo...

background or methods

On Darling–Robbins type confidence sequences and sequential tests with power one for parameters of an autoregressive process

Towards Enhancement of the Economy of a Thermal Power Generating System through Prediction of Plant Efficiency

Study of the collection, analysis, interpretation, and presentation of data

On Darling–Robbins type confidence sequences and sequential tests with power one for parameters of an autoregressive process

Citations

Towards Enhancement of the Economy of a Thermal Power Generating System through Prediction of Plant Efficiency

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